Why Stock Markets Crash is a difficult book to categorise. It
is not a get rich quick guide, nor is it a standard financial economics
text or a scientific monograph. It is aimed at the general reader, but
reads like a deep scientific text while tackling a classic economic problem.
This diversity of influences arises because the author is working at
the rapidly expanding interface between economics and the natural sciences.

The book is immediately distinctive because of the background of its
author. Didier Sornette is not an economist, but a geophysicist. His
previous work has concentrated on the behaviour of complex natural systems
under stress. Sornette’s perspective as an outsider is part of
what makes the book such interesting reading—he uses the cutting
edge tools of the natural sciences, most of which have not found their
way into economics. In particular, he applies some advanced mathematical
methods used to analyse catastrophic natural events such as earthquakes
and volcanic activity, to examining the great catastrophe of modern economies:
the stock market crash.

On methodological grounds alone, Sornette’s book is a valuable
addition to the financial literature, because most economic studies use
old-fashioned linear models mostly long abandoned by the natural sciences.
The few nonlinear models actually used in finance do not fit the data
particularly well, as Sornette points out. They especially underestimate
the risk of crashes.

Sornette’s main argument is that crashes are not—as the
media propounds after they happen—the result of immediate news-related ‘causes’ alone.
Instead, crashes are the result of growing instability in the market
system, the outcome of a long build-up of herd behaviour that forces
the market into an increasingly precarious position. Once the system
has reached a ‘critical point’ where instability is at its
peak, even a small stimulus can cause a crash. However, the real blame
should lie not with any news-related stimulus, but with the unstable
nature of the market system under stress.

The first part of Sornette’s thesis is that financial crashes
are ‘outliers’, which have their own statistical signatures.
This departs from the standard finance view that big price drops are
just ‘small drops that did not stop’ (p. 26), with no other
distinguishing or predictable features. The specific statistical character
of crashes means that they must be analysed separately from other market
movements, but it also means that they can be tracked, and to some extent
predicted. To demonstrate this, Sornette establishes the distinctive
character of large market movements, using examples from markets across
the world.

The second plank of his argument is that before crashes, market movements
can be approximately described by a process known as log-periodicity.
Roughly speaking, log-periodicity is a series of oscillations that become
more and more rapid before a crash. Log-periodicity is significant because
it seems to emerge only in the lead-up to a crash and not at other times;
hence its presence is an important signal that a crash may be imminent.
Sornette specifies and tests gradually more refined models of the process
on crashes in different markets throughout the world, making and testing
predictions about real markets movements. This is the most mathematically
demanding part of the book, but Sornette tries very hard to explain the
results intuitively, and keeps the equations to a minimum in technical
inserts.

Interestingly, the crash predictions Sornette makes using log-periodicity
models actually test out reasonably well, but his framework is still
a long way from forecasting crashes. The market’s direction cannot
be predicted with these models at any time frame more than a year out,
and even with detailed price data, they can only predict a crash to within
a few weeks, if it happens at all. Only three out of six of Sornette
and his past coauthors’ public predictions of a crash have come
to pass. As Sornette points out, that track record is not as statistically
unfavourable as it looks, given how few months crashes actually occur
in, but the framework is still far from completely robust. Even so, Sornette’s
work is likely to improve economists’ ability to track crashes
in advance.

As well as being highly original, Sornette’s findings provide
fascinating insight into dynamic market behaviour under stress. The behaviour
of stock markets is not smooth, rational and self-adjusting, as standard
equilibrium-based market models would have it. Instead, they are subject
to positive feedbacks (price changes feeding on themselves), they often
move in the absence of any changes in information, and they behave chaotically
under stress. This research is a clear advance on how to understand market
behaviour. Indirectly, this book underscores why it is valuable to study
financial markets. If the most liquid markets in the world—perhaps
the closest thing we have to a truly free market—can behave in
such a volatile, out-of-equilibrium fashion, and generate such unstable
outcomes, what does that imply about the quality of markets as a method
of economic organisation more generally? All economists, indeed, anyone
with an interest in economic matters, should be concerned about this
question.

Sornette concludes with an interesting prediction for the next century,
making a bold call for the end of the ‘growth era’ around
2050. His prognosis is based on the observation that crashes tend to
take place after the market has spent some time increasing at increasing
rate—following a log-periodic trend. Crashes aside, during the
last two centuries all major financial indices have advanced at a faster-than-exponential
trend rate, as have population and GDP growth. The log-periodic model
implies that this trajectory is unsustainable and that the world economy,
as well as the market, may cease to grow or even slump heavily in the
middle of the next century. Such predictions are worth keeping an eye
out for in 50 years time. However, nonlinear dynamic models like the
log-periodic one Sornette uses tend to lose predictive power over long
horizons fairly quickly, so we should view his prediction somewhat sceptically.

The book focuses on the observed aggregate behaviour of markets as systems;
it does not really address the question of what makes individual traders
act like they do. Unfortunately, in this way, it resembles standard finance
arguments—expressed with dazzling mathematical beauty and impressive
quantitative firepower, but with people almost entirely left out of the
analysis. A commonly-heard quip is that most finance theories would not
change much if markets were populated solely by robots. Sornette puts
the question of underlying causes into a black box of blaming the sometimes
unstable nature of the market system. But if volatility is the fault
of the system, then what factor(s) are causing instability? Sornette
surveys the economics literature on ‘rational bubbles’ and
some of the newer ‘behavioural finance’, in an attempt to
cover the established theories of trader behaviour, but he doesn’t
reach any firm conclusions. I happen to be quite partial to the behavioural
finance literature, which uses insights from cognitive psychology to
help explain investor behaviour and thereby brings people back into the
analysis, and it may provide some answers as to how and why bubbles begin
to inflate and deflate. For interested readers, Shleifer (2000) is a
good overview of the field.

Within the behavioural literature, recent research into why bubbles
arise and, more pertinently for our purposes, why they burst, complements
Sornette’s argument well. Abreu & Brunnermeier (2003), for
example, reject the orthodox finance argument that bubbles burst when
rational traders finally obtain the upper hand in the market and move
prices back to their appropriate level. Rather, they argue, bubbles burst
simply because a herd of uninformed traders all happen to react at the
same time to the same piece of information, or to some other stimulus
such a price fall below a ‘psychological barrier’. Trader
behaviour may be the immediate ‘cause’ of the crash, after
the system has reached a critical point. Further research along these
lines is an obvious way forward from Sornette’s findings.

Why Stock Markets Crash is
not for those whose eyes glaze over at the sight of a pronumeral.

However, interesting as its empirical work and mathematical setting
are, the book’s argument suffers from a few theoretical problems
irksome to one familiar with recent advances in financial economics.
The most frustrating is that Sornette places excessive faith in the concept
of stock market efficiency. This is the notion that a stock’s price
accurately reflects all available information about the stock. Efficiency
is said to be enforced by arbitrage, that is, by smart investors trading
against the market to correct inaccurate prices. While formerly considered
almost a gospel truth within the finance profession, market efficiency
has come under sustained empirical and theoretical attack over the last
two decades (see, for example, Lamont & Thaler (2003) and Rashes
(2001) for some spectacular examples of the failure of arbitrage to correct
unambiguous instances of mispricing). Nor does Sornette consider the
implications for market efficiency of the very existence of crashes,
which often occur in the absence of any news events. In fact, the crash
of 1987 was responsible for a new wave of literature casting doubt on
the theory of efficient markets. For a book that is so refreshingly new
in other ways, its subscription to an old theory on the empirical back
foot is disappointing.

Further, Sornette seems unaware of some not-so-recent research demonstrating
emphatically that stock price movements are not random, but are somewhat
predictable over short and medium term horizons (the classic references
are Lo & MacKinlay (1988) for the short term, and De Bondt & Thaler
(1985) for the medium term). He uses the standard ‘random walk’ setting
constantly, even after demonstrating that large price changes take place
far too often for market movements to be truly random, given the market’s
average return and standard deviation. This is a problem with Sornette’s
theory, given that random prices are supposed to be a sign of market
efficiency, and randomness is the major plank of the evidence for efficiency
he uses. Admittedly, the random walk assumption does not seem to affect
the results of the empirical work, but given the otherwise boldly original
nature of the book, again, the use of an empirically questionable framework
is jarring.

Another shortcoming of the book is that it does not much address what
might be done to contain crashes. Sornette seems to subscribe to a mild laissez-faire approach,
leaning towards the view that it is better not to interfere in the operations
of a complex system, lest the intervention precipitate an even more catastrophic
outcome later. At one point he draws an analogy with forest fires, noting
that when fires are allowed to burn without hazard control, they paradoxically
tend to be smaller and cause less damage than fires that have been deprived
of fuel through backburning. Similarly, the use of ‘circuit breakers’ and
enforced trading halts in financial markets have generally been found
not to reduce market fluctuations and are actually associated with an
increase in volatility. While this half-answer is unsatisfying, it is
the only one Sornette provides. This is clearly an avenue for future
research in light of the book’s findings on market dynamics.

Why Stock Markets Crash is not a book for those who want to learn
how to cash in by bailing out of the market the minute before a crash.
Nor is it suitable for those whose eyes glaze over at the sight of a
pronumeral. But it is an interesting application of new scientific tools
to an old economic problem, and it provides clear lessons about how financial
markets behave under stress. Despite its theoretical limitations, it
is to be hoped that members of the finance and economics professions
will attend both to the empirical findings of this book, and to its distinctive
method of undertaking financial research.

Zach Alexopoulos is
an honours student in political economy at The University of Sydney.
His thesis deals with the causes of stock market volatility and market-level
policies for reducing it. Thanks to Rita Bhattacharya and Roni Demirbag
for helpful comments.